FOWTs pose several control challenges. This work addresses reduced order modelling of FOWT to develop an MPC. They key objective is tackle the platform pitch instability while improving the performance in other KPIs. An existing reduced order model, which considers platform pitch and surge, and rotor speed DOFs is adapted and extended, with tower flexibility. The models are validated with open and closed-loop simulations in HAWC2, using the IEA-15MW RWT and the WindCrete spar-buoy floater. Based on these models, an ADKF is designed to estimate several unmeasured states and the wind speed. The MPC aims at reducing the platform pitch motion and tracking the reference rotor speed utilising collective blade pitch angle. The proposed holistic weight tuning procedure conveys the use of Pareto fronts and metrics from several relevant KPIs to guarantee an effective trade-off. Results show a major effects of the simulated wind conditions on the optimal tuning, therefore the process should account for realistic met-ocean conditions. The final tuning is compared to the baseline PI controller with torque compensation. Significant improvements are observed in terms of platform motion reduction in surge, pitch and roll, improved power quality, and greatly reduced fatigue and extreme loads on the tower base and shaft, under all simulated wind conditions. Limitations on rotor speed tracking near rated wind speed show that further development could lead to increase performance.

Floating Offshore Wind Turbines (FOWTs) pave the way to accessing deep water regions with abundant wind resources that are unreachable to bottom-fixed turbines. This technology is not widely deployed due to the increased cost of producing energy. A suitable control strategy can improve the power quality and extend the lifespan of the FOWT, resulting in a reduction of the final cost of energy. However, FOWTs face a specific set of control challenges in the above-rated operational region, such as the negative damping issue, rough environmental conditions, and increased model complexity due to both the floating structure and the increase in wind turbine size. Advanced control strategies are the most suited to resolve the negative damping problem, but obtaining a control model that balances low complexity with good accuracy is an increasingly difficult task. To mitigate the effect of environmental disturbances, feedforward control using wind preview is most commonly employed. Although waves have been shown to increase rotor speed oscillations and turbine loads, wave preview-based methods remain scarce. This thesis implements a model-free, feedforward controller based on wave preview for the above-rated region of a FOWT. The controller uses a preview of wave forces acting on the floating platform and aims for simultaneous rotor speed regulation and platform motion reduction using collective blade pitch control. As a model-free approach, a modified Data-enabled Predictive Control formulation that considers past and future information about measurable disturbances is proposed. The controller is implemented with a linear model of the NREL 5-MW wind turbine installed on the OC3-Hywind spar-buoy platform and tested in several cases. The effectiveness of the wave feedforward data-driven controller is evaluated in a high-fidelity environment using the QBlade simulator. A decrease in rotor speed variance of 67% and platform pitching motions of 71% is obtained, at the cost of a 7-fold increase in blade pitching effort compared to the baseline controller. In turbulent wind conditions, the wind proved to be the dominant disturbance, and including both wind and wave previews in the controller is recommended. This work demonstrated the feasibility of a model-free feedforward control strategy for wave effect mitigation in FOWTs. Further efforts are required to adapt this strategy to closed-loop operation and to validate its effectiveness across the entirety of the above-rated region.